Overview

Brought to you by YData

Dataset statistics

Number of variables31
Number of observations85103
Missing cells272781
Missing cells (%)10.3%
Duplicate rows5
Duplicate rows (%)< 0.1%
Total size in memory19.1 MiB
Average record size in memory235.0 B

Variable types

Text11
DateTime1
Categorical2
Numeric14
Boolean3

Alerts

Dataset has 5 (< 0.1%) duplicate rowsDuplicates
Estimated owners is highly imbalanced (53.6%)Imbalance
Windows is highly imbalanced (99.5%)Imbalance
About the game has 3567 (4.2%) missing valuesMissing
Reviews has 75360 (88.6%) missing valuesMissing
Score rank has 85059 (99.9%) missing valuesMissing
Notes has 72082 (84.7%) missing valuesMissing
Developers has 3587 (4.2%) missing valuesMissing
Publishers has 3867 (4.5%) missing valuesMissing
Categories has 4598 (5.4%) missing valuesMissing
Genres has 3555 (4.2%) missing valuesMissing
Tags has 21100 (24.8%) missing valuesMissing
Peak CCU is highly skewed (γ1 = 116.3632974)Skewed
Price is highly skewed (γ1 = 23.00630262)Skewed
DLC count is highly skewed (γ1 = 121.2792744)Skewed
User score is highly skewed (γ1 = 46.69189223)Skewed
Positive is highly skewed (γ1 = 165.7952261)Skewed
Negative is highly skewed (γ1 = 150.2675238)Skewed
Achievements is highly skewed (γ1 = 27.06595488)Skewed
Recommendations is highly skewed (γ1 = 109.4463242)Skewed
Average playtime forever is highly skewed (γ1 = 58.96988105)Skewed
Average playtime two weeks is highly skewed (γ1 = 45.01545969)Skewed
Median playtime forever is highly skewed (γ1 = 79.54832202)Skewed
Median playtime two weeks is highly skewed (γ1 = 41.80555858)Skewed
Peak CCU has 62436 (73.4%) zerosZeros
Required age has 83463 (98.1%) zerosZeros
Price has 16461 (19.3%) zerosZeros
DLC count has 73263 (86.1%) zerosZeros
Metacritic score has 81191 (95.4%) zerosZeros
User score has 85059 (99.9%) zerosZeros
Positive has 23314 (27.4%) zerosZeros
Negative has 33951 (39.9%) zerosZeros
Achievements has 43345 (50.9%) zerosZeros
Recommendations has 71343 (83.8%) zerosZeros
Average playtime forever has 70192 (82.5%) zerosZeros
Average playtime two weeks has 83048 (97.6%) zerosZeros
Median playtime forever has 70192 (82.5%) zerosZeros
Median playtime two weeks has 83048 (97.6%) zerosZeros

Reproduction

Analysis started2024-09-14 16:48:11.879014
Analysis finished2024-09-14 16:50:59.269478
Duration2 minutes and 47.39 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Name
Text

Distinct84367
Distinct (%)99.1%
Missing6
Missing (%)< 0.1%
Memory size1.3 MiB
2024-09-14T16:50:59.778673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length184
Median length117
Mean length17.945309
Min length1

Characters and Unicode

Total characters1527092
Distinct characters3080
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83759 ?
Unique (%)98.4%

Sample

1st rowGalactic Bowling
2nd rowTrain Bandit
3rd rowJolt Project
4th rowHenosis™
5th rowTwo Weeks in Painland
ValueCountFrequency (%)
the 11076
 
4.5%
of 7193
 
2.9%
5654
 
2.3%
playtest 3383
 
1.4%
2 2283
 
0.9%
vr 2085
 
0.8%
a 1761
 
0.7%
and 1546
 
0.6%
edition 1472
 
0.6%
in 1325
 
0.5%
Other values (46696) 209883
84.7%
2024-09-14T16:51:00.803695image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162649
 
10.7%
e 133875
 
8.8%
a 94359
 
6.2%
o 84738
 
5.5%
r 82728
 
5.4%
i 78122
 
5.1%
t 76783
 
5.0%
n 70755
 
4.6%
s 62227
 
4.1%
l 57544
 
3.8%
Other values (3070) 623312
40.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1527092
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
162649
 
10.7%
e 133875
 
8.8%
a 94359
 
6.2%
o 84738
 
5.5%
r 82728
 
5.4%
i 78122
 
5.1%
t 76783
 
5.0%
n 70755
 
4.6%
s 62227
 
4.1%
l 57544
 
3.8%
Other values (3070) 623312
40.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1527092
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
162649
 
10.7%
e 133875
 
8.8%
a 94359
 
6.2%
o 84738
 
5.5%
r 82728
 
5.4%
i 78122
 
5.1%
t 76783
 
5.0%
n 70755
 
4.6%
s 62227
 
4.1%
l 57544
 
3.8%
Other values (3070) 623312
40.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1527092
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
162649
 
10.7%
e 133875
 
8.8%
a 94359
 
6.2%
o 84738
 
5.5%
r 82728
 
5.4%
i 78122
 
5.1%
t 76783
 
5.0%
n 70755
 
4.6%
s 62227
 
4.1%
l 57544
 
3.8%
Other values (3070) 623312
40.8%
Distinct4401
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
Minimum1997-06-30 00:00:00
Maximum2025-04-14 00:00:00
2024-09-14T16:51:01.132962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:51:01.446402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Estimated owners
Categorical

IMBALANCE 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
0 - 20000
55285 
0 - 0
11504 
20000 - 50000
7808 
50000 - 100000
 
3886
100000 - 200000
 
2566
Other values (9)
 
4054

Length

Max length21
Median length9
Mean length9.5582647
Min length5

Characters and Unicode

Total characters813437
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0 - 20000
2nd row0 - 20000
3rd row0 - 20000
4th row0 - 20000
5th row0 - 20000

Common Values

ValueCountFrequency (%)
0 - 20000 55285
65.0%
0 - 0 11504
 
13.5%
20000 - 50000 7808
 
9.2%
50000 - 100000 3886
 
4.6%
100000 - 200000 2566
 
3.0%
200000 - 500000 2142
 
2.5%
500000 - 1000000 906
 
1.1%
1000000 - 2000000 521
 
0.6%
2000000 - 5000000 329
 
0.4%
5000000 - 10000000 92
 
0.1%
Other values (4) 64
 
0.1%

Length

2024-09-14T16:51:01.746766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
85103
33.3%
0 78293
30.7%
20000 63093
24.7%
50000 11694
 
4.6%
100000 6452
 
2.5%
200000 4708
 
1.8%
500000 3048
 
1.2%
1000000 1427
 
0.6%
2000000 850
 
0.3%
5000000 421
 
0.2%
Other values (5) 220
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 466215
57.3%
170206
 
20.9%
- 85103
 
10.5%
2 68711
 
8.4%
5 15188
 
1.9%
1 8014
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 813437
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 466215
57.3%
170206
 
20.9%
- 85103
 
10.5%
2 68711
 
8.4%
5 15188
 
1.9%
1 8014
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 813437
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 466215
57.3%
170206
 
20.9%
- 85103
 
10.5%
2 68711
 
8.4%
5 15188
 
1.9%
1 8014
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 813437
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 466215
57.3%
170206
 
20.9%
- 85103
 
10.5%
2 68711
 
8.4%
5 15188
 
1.9%
1 8014
 
1.0%

Peak CCU
Real number (ℝ)

SKEWED  ZEROS 

Distinct1445
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.87293
Minimum0
Maximum872138
Zeros62436
Zeros (%)73.4%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:02.041376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile36
Maximum872138
Range872138
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5403.5489
Coefficient of variation (CV)40.063998
Kurtosis16368.39
Mean134.87293
Median Absolute Deviation (MAD)0
Skewness116.3633
Sum11478091
Variance29198340
MonotonicityNot monotonic
2024-09-14T16:51:02.349123image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 62436
73.4%
1 7087
 
8.3%
2 2845
 
3.3%
3 1596
 
1.9%
4 1146
 
1.3%
5 836
 
1.0%
6 619
 
0.7%
7 486
 
0.6%
8 381
 
0.4%
9 313
 
0.4%
Other values (1435) 7358
 
8.6%
ValueCountFrequency (%)
0 62436
73.4%
1 7087
 
8.3%
2 2845
 
3.3%
3 1596
 
1.9%
4 1146
 
1.3%
5 836
 
1.0%
6 619
 
0.7%
7 486
 
0.6%
8 381
 
0.4%
9 313
 
0.4%
ValueCountFrequency (%)
872138 1
< 0.1%
825215 1
< 0.1%
558759 1
< 0.1%
405191 1
< 0.1%
287501 1
< 0.1%
275374 1
< 0.1%
235067 1
< 0.1%
233454 1
< 0.1%
170527 1
< 0.1%
169110 1
< 0.1%

Required age
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.31277393
Minimum0
Maximum21
Zeros83463
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:02.611262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.2547206
Coefficient of variation (CV)7.2087869
Kurtosis49.816737
Mean0.31277393
Median Absolute Deviation (MAD)0
Skewness7.1635607
Sum26618
Variance5.0837652
MonotonicityNot monotonic
2024-09-14T16:51:02.873441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 83463
98.1%
17 919
 
1.1%
18 333
 
0.4%
13 204
 
0.2%
16 68
 
0.1%
10 35
 
< 0.1%
12 34
 
< 0.1%
3 8
 
< 0.1%
15 8
 
< 0.1%
7 7
 
< 0.1%
Other values (9) 24
 
< 0.1%
ValueCountFrequency (%)
0 83463
98.1%
1 1
 
< 0.1%
3 8
 
< 0.1%
5 1
 
< 0.1%
6 6
 
< 0.1%
7 7
 
< 0.1%
9 1
 
< 0.1%
10 35
 
< 0.1%
11 1
 
< 0.1%
12 34
 
< 0.1%
ValueCountFrequency (%)
21 5
 
< 0.1%
20 2
 
< 0.1%
19 1
 
< 0.1%
18 333
 
0.4%
17 919
1.1%
16 68
 
0.1%
15 8
 
< 0.1%
14 6
 
< 0.1%
13 204
 
0.2%
12 34
 
< 0.1%

Price
Real number (ℝ)

SKEWED  ZEROS 

Distinct584
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1937027
Minimum0
Maximum999.98
Zeros16461
Zeros (%)19.3%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:03.141479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.99
median4.49
Q39.99
95-th percentile19.99
Maximum999.98
Range999.98
Interquartile range (IQR)9

Descriptive statistics

Standard deviation12.362478
Coefficient of variation (CV)1.7185139
Kurtosis1521.6156
Mean7.1937027
Median Absolute Deviation (MAD)4
Skewness23.006303
Sum612205.68
Variance152.83086
MonotonicityNot monotonic
2024-09-14T16:51:03.455190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16461
19.3%
4.99 7752
 
9.1%
9.99 7199
 
8.5%
0.99 6497
 
7.6%
1.99 5192
 
6.1%
2.99 4852
 
5.7%
3.99 3561
 
4.2%
14.99 3524
 
4.1%
19.99 3326
 
3.9%
5.99 2549
 
3.0%
Other values (574) 24190
28.4%
ValueCountFrequency (%)
0 16461
19.3%
0.29 1
 
< 0.1%
0.35 1
 
< 0.1%
0.37 1
 
< 0.1%
0.44 1
 
< 0.1%
0.49 614
 
0.7%
0.5 45
 
0.1%
0.51 102
 
0.1%
0.52 1
 
< 0.1%
0.53 7
 
< 0.1%
ValueCountFrequency (%)
999.98 2
 
< 0.1%
999 1
 
< 0.1%
299.9 1
 
< 0.1%
269.99 1
 
< 0.1%
249 1
 
< 0.1%
199.99 58
0.1%
164.34 1
 
< 0.1%
149.99 15
 
< 0.1%
134.1 1
 
< 0.1%
129.99 7
 
< 0.1%

DLC count
Real number (ℝ)

SKEWED  ZEROS 

Distinct95
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5434121
Minimum0
Maximum2366
Zeros73263
Zeros (%)86.1%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:03.862321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2366
Range2366
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.721223
Coefficient of variation (CV)25.250123
Kurtosis17698.545
Mean0.5434121
Median Absolute Deviation (MAD)0
Skewness121.27927
Sum46246
Variance188.27195
MonotonicityNot monotonic
2024-09-14T16:51:04.286345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 73263
86.1%
1 7596
 
8.9%
2 1884
 
2.2%
3 716
 
0.8%
4 395
 
0.5%
5 255
 
0.3%
6 150
 
0.2%
7 118
 
0.1%
8 105
 
0.1%
10 72
 
0.1%
Other values (85) 549
 
0.6%
ValueCountFrequency (%)
0 73263
86.1%
1 7596
 
8.9%
2 1884
 
2.2%
3 716
 
0.8%
4 395
 
0.5%
5 255
 
0.3%
6 150
 
0.2%
7 118
 
0.1%
8 105
 
0.1%
9 68
 
0.1%
ValueCountFrequency (%)
2366 1
 
< 0.1%
1968 1
 
< 0.1%
1555 1
 
< 0.1%
678 5
< 0.1%
579 1
 
< 0.1%
461 1
 
< 0.1%
386 1
 
< 0.1%
343 1
 
< 0.1%
260 1
 
< 0.1%
214 1
 
< 0.1%

About the game
Text

MISSING 

Distinct81100
Distinct (%)99.5%
Missing3567
Missing (%)4.2%
Memory size1.3 MiB
2024-09-14T16:51:05.578815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length95883
Median length4602
Mean length1257.6859
Min length1

Characters and Unicode

Total characters102546681
Distinct characters8744
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80910 ?
Unique (%)99.2%

Sample

1st rowGalactic Bowling is an exaggerated and stylized bowling game with an intergalactic twist. Players will engage in fast-paced single and multi-player competition while being submerged in a unique new universe filled with over-the-top humor, wild characters, unique levels, and addictive game play. The title is aimed at players of all ages and skill sets. Through accessible and intuitive controls and game-play, Galactic Bowling allows you to jump right into the action. A single-player campaign and online play allow you to work your way up the ranks of the Galactic Bowling League! Whether you have hours to play or only a few minutes, Galactic Bowling is a fast paced and entertaining experience that will leave you wanting more! Full Single-player story campaign including 11 Characters and Environments. 2 Single-player play modes including Regular and Battle Modes. Head to Head Online Multiplayer play Modes. Super Powers, Special Balls, and Whammies. Unlockable Characters, Environments, and Minigames. Unlock all 30 Steam Achievements!
2nd rowTHE LAW!! Looks to be a showdown atop a train. This will be your last fight. Good luck, Train Bandit. WHAT IS THIS GAME? Train Bandit is a simple score attack game. The Law will attack you from both sides. Your weapon is your keyboard. You'll use those keys to kick the living shit out of the law. React quickly by attacking the correct direction. React...or you're dead. THE FEATURES Unlock new bandits Earn Achievements Become Steam's Most Wanted ? Battle elite officers Kick the law's ass
3rd rowJolt Project: The army now has a new robotics project, jolt. It's up to you to control it and ensure the success of the missions! There are 9 stages of taking the breath away with the right difficulty and good gameplay. Plus an insane way of survival! Fire missiles at cars, tanks, helicopters and turrets! The fun is guaranteed! Use your mouse to aim and shoot and take out the enemies! In this game you will have to be aware of the various enemies who will do everything to destroy your charges and prevent the success of your mission! Cartoon-style graphics are optimized and fun and generate an excellent gaming environment!
4th rowHENOSIS™ is a mysterious 2D Platform Puzzler where players are propelled into weird and visceral worlds as they take control of a small, droplet of water while overcoming obstacles and enemies throughout each level. The Player must venture through each world as it collects precious water tokens in order open the exit portal and restore vitality to its drought-ridden home world. Features: Traverse your way through 27 hand-crafted levels Unique player mechanics Battle menacing bosses across 3 distinct worlds* Original artwork &amp; animation Full controller support Localization support * Hidden world included!
5th rowABOUT THE GAME Play as a hacker who has arranged a deal with a gangster. That’s how the protagonist, Jack, is assigned a mission that should be accomplished in a specific timeframe, which he will find out soon enough. THE GAME’S FEATURES Spy on 4 senior managers within an organization to find out about their personalities. Manage the recruitment process in the organization to improve the work climate. Hack the candidates who want to get into the organization to make your job easier. Try to avoid having your physical health impacted negatively in the process. All of this while you enjoy an interesting story full of humor and action that evolves along with the game.
ValueCountFrequency (%)
the 904428
 
5.3%
and 599695
 
3.5%
to 518598
 
3.0%
of 411839
 
2.4%
a 406089
 
2.4%
you 310387
 
1.8%
in 257803
 
1.5%
your 236294
 
1.4%
is 194587
 
1.1%
with 189548
 
1.1%
Other values (291815) 13030532
76.4%
2024-09-14T16:51:07.372794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16974421
16.6%
e 9623845
 
9.4%
t 6493977
 
6.3%
a 6450170
 
6.3%
o 6087491
 
5.9%
n 5365015
 
5.2%
i 5338203
 
5.2%
s 5037212
 
4.9%
r 5017214
 
4.9%
l 3692354
 
3.6%
Other values (8734) 32466779
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 102546681
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
16974421
16.6%
e 9623845
 
9.4%
t 6493977
 
6.3%
a 6450170
 
6.3%
o 6087491
 
5.9%
n 5365015
 
5.2%
i 5338203
 
5.2%
s 5037212
 
4.9%
r 5017214
 
4.9%
l 3692354
 
3.6%
Other values (8734) 32466779
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 102546681
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
16974421
16.6%
e 9623845
 
9.4%
t 6493977
 
6.3%
a 6450170
 
6.3%
o 6087491
 
5.9%
n 5365015
 
5.2%
i 5338203
 
5.2%
s 5037212
 
4.9%
r 5017214
 
4.9%
l 3692354
 
3.6%
Other values (8734) 32466779
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 102546681
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
16974421
16.6%
e 9623845
 
9.4%
t 6493977
 
6.3%
a 6450170
 
6.3%
o 6087491
 
5.9%
n 5365015
 
5.2%
i 5338203
 
5.2%
s 5037212
 
4.9%
r 5017214
 
4.9%
l 3692354
 
3.6%
Other values (8734) 32466779
31.7%
Distinct11306
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:07.881320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1216
Median length11
Mean length48.66624
Min length2

Characters and Unicode

Total characters4141643
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9479 ?
Unique (%)11.1%

Sample

1st row['English']
2nd row['English', 'French', 'Italian', 'German', 'Spanish - Spain', 'Japanese', 'Portuguese - Brazil', 'Russian', 'Simplified Chinese', 'Traditional Chinese']
3rd row['English', 'Portuguese - Brazil']
4th row['English', 'French', 'Italian', 'German', 'Spanish - Spain', 'Japanese', 'Korean', 'Portuguese', 'Russian', 'Simplified Chinese', 'Traditional Chinese']
5th row['English', 'Spanish - Spain']
ValueCountFrequency (%)
english 78062
18.6%
36050
 
8.6%
chinese 28882
 
6.9%
spanish 21223
 
5.1%
simplified 19307
 
4.6%
german 18649
 
4.4%
french 18071
 
4.3%
russian 17383
 
4.1%
spain 16706
 
4.0%
portuguese 15515
 
3.7%
Other values (134) 149786
35.7%
2024-09-14T16:51:09.305433image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 633750
15.3%
i 339688
 
8.2%
334532
 
8.1%
n 302345
 
7.3%
a 245342
 
5.9%
, 235265
 
5.7%
s 224621
 
5.4%
e 222250
 
5.4%
h 186366
 
4.5%
l 149367
 
3.6%
Other values (57) 1268117
30.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4141643
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 633750
15.3%
i 339688
 
8.2%
334532
 
8.1%
n 302345
 
7.3%
a 245342
 
5.9%
, 235265
 
5.7%
s 224621
 
5.4%
e 222250
 
5.4%
h 186366
 
4.5%
l 149367
 
3.6%
Other values (57) 1268117
30.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4141643
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 633750
15.3%
i 339688
 
8.2%
334532
 
8.1%
n 302345
 
7.3%
a 245342
 
5.9%
, 235265
 
5.7%
s 224621
 
5.4%
e 222250
 
5.4%
h 186366
 
4.5%
l 149367
 
3.6%
Other values (57) 1268117
30.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4141643
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 633750
15.3%
i 339688
 
8.2%
334532
 
8.1%
n 302345
 
7.3%
a 245342
 
5.9%
, 235265
 
5.7%
s 224621
 
5.4%
e 222250
 
5.4%
h 186366
 
4.5%
l 149367
 
3.6%
Other values (57) 1268117
30.6%
Distinct2240
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:09.801780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1216
Median length2
Mean length16.966593
Min length2

Characters and Unicode

Total characters1443908
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1668 ?
Unique (%)2.0%

Sample

1st row[]
2nd row[]
3rd row[]
4th row[]
5th row[]
ValueCountFrequency (%)
57188
31.6%
english 32200
17.8%
chinese 7789
 
4.3%
simplified 4979
 
2.7%
spanish 4964
 
2.7%
russian 4160
 
2.3%
japanese 4092
 
2.3%
german 3770
 
2.1%
portuguese 3646
 
2.0%
french 3473
 
1.9%
Other values (117) 54898
30.3%
2024-09-14T16:51:10.641094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 212748
14.7%
i 111920
 
7.8%
n 98017
 
6.8%
96056
 
6.7%
[ 85131
 
5.9%
] 85131
 
5.9%
a 78083
 
5.4%
s 73399
 
5.1%
, 70735
 
4.9%
h 63833
 
4.4%
Other values (54) 468855
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1443908
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 212748
14.7%
i 111920
 
7.8%
n 98017
 
6.8%
96056
 
6.7%
[ 85131
 
5.9%
] 85131
 
5.9%
a 78083
 
5.4%
s 73399
 
5.1%
, 70735
 
4.9%
h 63833
 
4.4%
Other values (54) 468855
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1443908
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 212748
14.7%
i 111920
 
7.8%
n 98017
 
6.8%
96056
 
6.7%
[ 85131
 
5.9%
] 85131
 
5.9%
a 78083
 
5.4%
s 73399
 
5.1%
, 70735
 
4.9%
h 63833
 
4.4%
Other values (54) 468855
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1443908
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 212748
14.7%
i 111920
 
7.8%
n 98017
 
6.8%
96056
 
6.7%
[ 85131
 
5.9%
] 85131
 
5.9%
a 78083
 
5.4%
s 73399
 
5.1%
, 70735
 
4.9%
h 63833
 
4.4%
Other values (54) 468855
32.5%

Reviews
Text

MISSING 

Distinct9646
Distinct (%)99.0%
Missing75360
Missing (%)88.6%
Memory size1.3 MiB
2024-09-14T16:51:11.201744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length2911
Median length882
Mean length349.40911
Min length2

Characters and Unicode

Total characters3404293
Distinct characters2423
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9580 ?
Unique (%)98.3%

Sample

1st row“New WW2 Strategy Game Offers A Harrowing Look At Poland's Ill-Fated 1944 Uprising” GameSpot “(…) in execution Warsaw manages to deliver its own experience entirely.” Dualshockers “(…) Beautiful hand-painted artwork and turn-based combat (…)” Gameinformer
2nd row“The art in Cthulhu Realms is hilarious and beautifully done, somehow complimenting the horror theme perfectly. The production value is top-notch.” Gameosity “It’s a surprisingly effective package that delivers a great little deck builder with a low price tag. If you can embrace the playful theme, you’ll find a pleasant gem in Cthulhu Realms.” Geek Ken “It certainly is not just another deck-building game, but has original and fresh mechanics that will challenge your brain.” Board Game Maniac
3rd row“Hero of the Kingdom II is a title that casual gamers should find to be very enjoyable, especially those who have appreciated the prequel.” 4.0/5 – Softpedia
4th row“Unhappy Ever After is the result of a wicked mind’s imagination!” 8/10 – OPN
5th row“Reigns: Game of Thrones is so much better than any other attempt to bring Game of Thrones to video games so far.” Digitally Downloaded “A Westerosi romp with welcome wrinkles to the established Reigns formula” Gamespot “Reigns is probably the best Game of Thrones game we’ve played to date.” Trusted Reviews
ValueCountFrequency (%)
the 21452
 
3.7%
a 17872
 
3.1%
and 16974
 
3.0%
of 15044
 
2.6%
to 11845
 
2.1%
11448
 
2.0%
is 11165
 
1.9%
game 8658
 
1.5%
in 6245
 
1.1%
that 5969
 
1.0%
Other values (46958) 446714
77.9%
2024-09-14T16:51:12.142725image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
563570
16.6%
e 308254
 
9.1%
a 219331
 
6.4%
t 216349
 
6.4%
i 181319
 
5.3%
o 180249
 
5.3%
n 168023
 
4.9%
s 157519
 
4.6%
r 146500
 
4.3%
l 119512
 
3.5%
Other values (2413) 1143667
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3404293
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
563570
16.6%
e 308254
 
9.1%
a 219331
 
6.4%
t 216349
 
6.4%
i 181319
 
5.3%
o 180249
 
5.3%
n 168023
 
4.9%
s 157519
 
4.6%
r 146500
 
4.3%
l 119512
 
3.5%
Other values (2413) 1143667
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3404293
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
563570
16.6%
e 308254
 
9.1%
a 219331
 
6.4%
t 216349
 
6.4%
i 181319
 
5.3%
o 180249
 
5.3%
n 168023
 
4.9%
s 157519
 
4.6%
r 146500
 
4.3%
l 119512
 
3.5%
Other values (2413) 1143667
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3404293
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
563570
16.6%
e 308254
 
9.1%
a 219331
 
6.4%
t 216349
 
6.4%
i 181319
 
5.3%
o 180249
 
5.3%
n 168023
 
4.9%
s 157519
 
4.6%
r 146500
 
4.3%
l 119512
 
3.5%
Other values (2413) 1143667
33.6%

Windows
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size748.0 KiB
True
85073 
False
 
30
ValueCountFrequency (%)
True 85073
> 99.9%
False 30
 
< 0.1%
2024-09-14T16:51:12.511984image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Mac
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size748.0 KiB
False
68710 
True
16393 
ValueCountFrequency (%)
False 68710
80.7%
True 16393
 
19.3%
2024-09-14T16:51:12.758487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Linux
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size748.0 KiB
False
73907 
True
11196 
ValueCountFrequency (%)
False 73907
86.8%
True 11196
 
13.2%
2024-09-14T16:51:13.008525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Metacritic score
Real number (ℝ)

ZEROS 

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3483661
Minimum0
Maximum97
Zeros81191
Zeros (%)95.4%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:13.288092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum97
Range97
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.421471
Coefficient of variation (CV)4.6056706
Kurtosis18.396785
Mean3.3483661
Median Absolute Deviation (MAD)0
Skewness4.4754037
Sum284956
Variance237.82178
MonotonicityNot monotonic
2024-09-14T16:51:13.595757image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 81191
95.4%
80 191
 
0.2%
76 171
 
0.2%
77 170
 
0.2%
78 166
 
0.2%
73 161
 
0.2%
81 161
 
0.2%
75 159
 
0.2%
72 151
 
0.2%
68 148
 
0.2%
Other values (63) 2434
 
2.9%
ValueCountFrequency (%)
0 81191
95.4%
20 1
 
< 0.1%
23 1
 
< 0.1%
24 1
 
< 0.1%
27 2
 
< 0.1%
29 2
 
< 0.1%
30 2
 
< 0.1%
32 2
 
< 0.1%
33 1
 
< 0.1%
34 3
 
< 0.1%
ValueCountFrequency (%)
97 2
 
< 0.1%
96 4
 
< 0.1%
95 2
 
< 0.1%
94 12
 
< 0.1%
93 14
 
< 0.1%
92 12
 
< 0.1%
91 26
< 0.1%
90 31
< 0.1%
89 41
< 0.1%
88 43
0.1%

User score
Real number (ℝ)

SKEWED  ZEROS 

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.039822333
Minimum0
Maximum100
Zeros85059
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:13.887299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.791013
Coefficient of variation (CV)44.975091
Kurtosis2246.5439
Mean0.039822333
Median Absolute Deviation (MAD)0
Skewness46.691892
Sum3389
Variance3.2077277
MonotonicityNot monotonic
2024-09-14T16:51:14.158592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 85059
99.9%
100 5
 
< 0.1%
80 2
 
< 0.1%
84 2
 
< 0.1%
46 2
 
< 0.1%
94 2
 
< 0.1%
51 2
 
< 0.1%
95 2
 
< 0.1%
68 2
 
< 0.1%
77 2
 
< 0.1%
Other values (23) 23
 
< 0.1%
ValueCountFrequency (%)
0 85059
99.9%
46 2
 
< 0.1%
51 2
 
< 0.1%
53 1
 
< 0.1%
55 1
 
< 0.1%
57 1
 
< 0.1%
59 1
 
< 0.1%
60 1
 
< 0.1%
61 1
 
< 0.1%
63 1
 
< 0.1%
ValueCountFrequency (%)
100 5
< 0.1%
98 1
 
< 0.1%
97 1
 
< 0.1%
96 1
 
< 0.1%
95 2
 
< 0.1%
94 2
 
< 0.1%
92 1
 
< 0.1%
88 1
 
< 0.1%
87 1
 
< 0.1%
84 2
 
< 0.1%

Positive
Real number (ℝ)

SKEWED  ZEROS 

Distinct4532
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean958.56089
Minimum0
Maximum5764420
Zeros23314
Zeros (%)27.4%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:14.482123image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q345
95-th percentile1229.9
Maximum5764420
Range5764420
Interquartile range (IQR)45

Descriptive statistics

Standard deviation24359.199
Coefficient of variation (CV)25.412261
Kurtosis37240.663
Mean958.56089
Median Absolute Deviation (MAD)7
Skewness165.79523
Sum81576407
Variance5.9337058 × 108
MonotonicityNot monotonic
2024-09-14T16:51:14.785949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23314
27.4%
1 5291
 
6.2%
2 3951
 
4.6%
3 3051
 
3.6%
4 2620
 
3.1%
5 2202
 
2.6%
6 1843
 
2.2%
7 1589
 
1.9%
8 1383
 
1.6%
9 1309
 
1.5%
Other values (4522) 38550
45.3%
ValueCountFrequency (%)
0 23314
27.4%
1 5291
 
6.2%
2 3951
 
4.6%
3 3051
 
3.6%
4 2620
 
3.1%
5 2202
 
2.6%
6 1843
 
2.2%
7 1589
 
1.9%
8 1383
 
1.6%
9 1309
 
1.5%
ValueCountFrequency (%)
5764420 1
< 0.1%
1477153 1
< 0.1%
1171197 1
< 0.1%
1154655 1
< 0.1%
964983 1
< 0.1%
929372 1
< 0.1%
823693 1
< 0.1%
822326 1
< 0.1%
703687 1
< 0.1%
619457 1
< 0.1%

Negative
Real number (ℝ)

SKEWED  ZEROS 

Distinct2303
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.77257
Minimum0
Maximum895978
Zeros33951
Zeros (%)39.9%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:15.108813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314
95-th percentile257
Maximum895978
Range895978
Interquartile range (IQR)14

Descriptive statistics

Standard deviation4574.5839
Coefficient of variation (CV)28.631848
Kurtosis26859.424
Mean159.77257
Median Absolute Deviation (MAD)2
Skewness150.26752
Sum13597125
Variance20926818
MonotonicityNot monotonic
2024-09-14T16:51:15.432631image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33951
39.9%
1 7998
 
9.4%
2 4854
 
5.7%
3 3347
 
3.9%
4 2641
 
3.1%
5 2030
 
2.4%
6 1713
 
2.0%
7 1472
 
1.7%
8 1257
 
1.5%
9 1140
 
1.3%
Other values (2293) 24700
29.0%
ValueCountFrequency (%)
0 33951
39.9%
1 7998
 
9.4%
2 4854
 
5.7%
3 3347
 
3.9%
4 2641
 
3.1%
5 2030
 
2.4%
6 1713
 
2.0%
7 1472
 
1.7%
8 1257
 
1.5%
9 1140
 
1.3%
ValueCountFrequency (%)
895978 1
< 0.1%
766677 1
< 0.1%
300437 1
< 0.1%
210154 1
< 0.1%
138530 1
< 0.1%
129925 1
< 0.1%
112924 1
< 0.1%
108223 1
< 0.1%
106038 1
< 0.1%
103661 1
< 0.1%

Score rank
Categorical

MISSING 

Distinct4
Distinct (%)9.1%
Missing85059
Missing (%)99.9%
Memory size1.3 MiB
99.0
18 
98.0
12 
100.0
12 
97.0

Length

Max length5
Median length4
Mean length4.2727273
Min length4

Characters and Unicode

Total characters188
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row98.0
2nd row98.0
3rd row99.0
4th row99.0
5th row100.0

Common Values

ValueCountFrequency (%)
99.0 18
 
< 0.1%
98.0 12
 
< 0.1%
100.0 12
 
< 0.1%
97.0 2
 
< 0.1%
(Missing) 85059
99.9%

Length

2024-09-14T16:51:15.734180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-14T16:51:16.013808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
99.0 18
40.9%
98.0 12
27.3%
100.0 12
27.3%
97.0 2
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 68
36.2%
9 50
26.6%
. 44
23.4%
8 12
 
6.4%
1 12
 
6.4%
7 2
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 188
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 68
36.2%
9 50
26.6%
. 44
23.4%
8 12
 
6.4%
1 12
 
6.4%
7 2
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 188
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 68
36.2%
9 50
26.6%
. 44
23.4%
8 12
 
6.4%
1 12
 
6.4%
7 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 188
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 68
36.2%
9 50
26.6%
. 44
23.4%
8 12
 
6.4%
1 12
 
6.4%
7 2
 
1.1%

Achievements
Real number (ℝ)

SKEWED  ZEROS 

Distinct431
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.859394
Minimum0
Maximum9821
Zeros43345
Zeros (%)50.9%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:16.309784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q318
95-th percentile53
Maximum9821
Range9821
Interquartile range (IQR)18

Descriptive statistics

Standard deviation171.44687
Coefficient of variation (CV)8.6330366
Kurtosis812.17535
Mean19.859394
Median Absolute Deviation (MAD)0
Skewness27.065955
Sum1690094
Variance29394.031
MonotonicityNot monotonic
2024-09-14T16:51:16.619685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43345
50.9%
10 2108
 
2.5%
12 1657
 
1.9%
20 1489
 
1.7%
6 1417
 
1.7%
15 1390
 
1.6%
5 1355
 
1.6%
8 1275
 
1.5%
11 1260
 
1.5%
9 1205
 
1.4%
Other values (421) 28602
33.6%
ValueCountFrequency (%)
0 43345
50.9%
1 893
 
1.0%
2 471
 
0.6%
3 649
 
0.8%
4 849
 
1.0%
5 1355
 
1.6%
6 1417
 
1.7%
7 1190
 
1.4%
8 1275
 
1.5%
9 1205
 
1.4%
ValueCountFrequency (%)
9821 1
 
< 0.1%
5394 1
 
< 0.1%
5000 59
0.1%
4999 1
 
< 0.1%
4997 1
 
< 0.1%
4996 1
 
< 0.1%
4989 1
 
< 0.1%
4987 2
 
< 0.1%
4981 1
 
< 0.1%
4979 1
 
< 0.1%

Recommendations
Real number (ℝ)

SKEWED  ZEROS 

Distinct4035
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean775.51757
Minimum0
Maximum3441592
Zeros71343
Zeros (%)83.8%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:16.976191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile960
Maximum3441592
Range3441592
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17893.375
Coefficient of variation (CV)23.072817
Kurtosis17671.765
Mean775.51757
Median Absolute Deviation (MAD)0
Skewness109.44632
Sum65998872
Variance3.2017288 × 108
MonotonicityNot monotonic
2024-09-14T16:51:17.493102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71343
83.8%
116 69
 
0.1%
106 65
 
0.1%
109 60
 
0.1%
105 60
 
0.1%
101 60
 
0.1%
127 59
 
0.1%
122 56
 
0.1%
135 55
 
0.1%
107 55
 
0.1%
Other values (4025) 13221
 
15.5%
ValueCountFrequency (%)
0 71343
83.8%
101 60
 
0.1%
102 52
 
0.1%
103 53
 
0.1%
104 51
 
0.1%
105 60
 
0.1%
106 65
 
0.1%
107 55
 
0.1%
108 47
 
0.1%
109 60
 
0.1%
ValueCountFrequency (%)
3441592 1
< 0.1%
1616422 1
< 0.1%
1247051 1
< 0.1%
899838 1
< 0.1%
899613 1
< 0.1%
899477 1
< 0.1%
899455 1
< 0.1%
899435 1
< 0.1%
783469 1
< 0.1%
725462 1
< 0.1%

Notes
Text

MISSING 

Distinct10570
Distinct (%)81.2%
Missing72082
Missing (%)84.7%
Memory size1.3 MiB
2024-09-14T16:51:18.217505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length2028
Median length707
Mean length137.54834
Min length2

Characters and Unicode

Total characters1791017
Distinct characters896
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9811 ?
Unique (%)75.3%

Sample

1st rowThis Game may contain content not appropriate for all ages, or may not be appropriate for viewing at work: violence, general Mature Content.
2nd rowThis game depicts sexual acts between the player and a female character. All characters depicted are over the age of 18.
3rd rowThis Game may contain content not appropriate for all ages, or may not be appropriate for viewing at work Download only for players over 18 years old.
4th rowIron Rebellion has elements of sci-fi combat with laser guns, missiles, and explosions.
5th rowPlease note that Who We Are Now contains explicit sexual scenes between men. These scenes are optional.
ValueCountFrequency (%)
and 11734
 
4.1%
the 9985
 
3.5%
game 9558
 
3.3%
of 8031
 
2.8%
content 6391
 
2.2%
this 5508
 
1.9%
sexual 5411
 
1.9%
for 5332
 
1.9%
in 5026
 
1.8%
not 4959
 
1.7%
Other values (10933) 213868
74.8%
2024-09-14T16:51:19.652424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
272779
15.2%
e 174757
 
9.8%
a 132355
 
7.4%
n 118743
 
6.6%
o 112053
 
6.3%
t 110090
 
6.1%
i 99769
 
5.6%
s 96900
 
5.4%
r 82057
 
4.6%
l 71621
 
4.0%
Other values (886) 519893
29.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1791017
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
272779
15.2%
e 174757
 
9.8%
a 132355
 
7.4%
n 118743
 
6.6%
o 112053
 
6.3%
t 110090
 
6.1%
i 99769
 
5.6%
s 96900
 
5.4%
r 82057
 
4.6%
l 71621
 
4.0%
Other values (886) 519893
29.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1791017
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
272779
15.2%
e 174757
 
9.8%
a 132355
 
7.4%
n 118743
 
6.6%
o 112053
 
6.3%
t 110090
 
6.1%
i 99769
 
5.6%
s 96900
 
5.4%
r 82057
 
4.6%
l 71621
 
4.0%
Other values (886) 519893
29.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1791017
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
272779
15.2%
e 174757
 
9.8%
a 132355
 
7.4%
n 118743
 
6.6%
o 112053
 
6.3%
t 110090
 
6.1%
i 99769
 
5.6%
s 96900
 
5.4%
r 82057
 
4.6%
l 71621
 
4.0%
Other values (886) 519893
29.0%

Average playtime forever
Real number (ℝ)

SKEWED  ZEROS 

Distinct2209
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.72968
Minimum0
Maximum145727
Zeros70192
Zeros (%)82.5%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:20.230888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile353
Maximum145727
Range145727
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1142.4475
Coefficient of variation (CV)10.908536
Kurtosis5295.1895
Mean104.72968
Median Absolute Deviation (MAD)0
Skewness58.969881
Sum8912810
Variance1305186.3
MonotonicityNot monotonic
2024-09-14T16:51:20.562901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 70192
82.5%
1 342
 
0.4%
2 133
 
0.2%
4 106
 
0.1%
3 105
 
0.1%
5 100
 
0.1%
6 96
 
0.1%
9 88
 
0.1%
8 87
 
0.1%
7 84
 
0.1%
Other values (2199) 13770
 
16.2%
ValueCountFrequency (%)
0 70192
82.5%
1 342
 
0.4%
2 133
 
0.2%
3 105
 
0.1%
4 106
 
0.1%
5 100
 
0.1%
6 96
 
0.1%
7 84
 
0.1%
8 87
 
0.1%
9 88
 
0.1%
ValueCountFrequency (%)
145727 1
< 0.1%
104238 1
< 0.1%
90351 1
< 0.1%
76068 1
< 0.1%
68357 1
< 0.1%
68159 1
< 0.1%
64973 1
< 0.1%
51388 1
< 0.1%
49555 1
< 0.1%
47336 1
< 0.1%

Average playtime two weeks
Real number (ℝ)

SKEWED  ZEROS 

Distinct781
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.680105
Minimum0
Maximum19159
Zeros83048
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:20.900404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum19159
Range19159
Interquartile range (IQR)0

Descriptive statistics

Standard deviation188.84001
Coefficient of variation (CV)17.681474
Kurtosis2786.2144
Mean10.680105
Median Absolute Deviation (MAD)0
Skewness45.01546
Sum908909
Variance35660.548
MonotonicityNot monotonic
2024-09-14T16:51:21.230436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 83048
97.6%
1 74
 
0.1%
2 24
 
< 0.1%
3 24
 
< 0.1%
8 21
 
< 0.1%
4 20
 
< 0.1%
10 19
 
< 0.1%
5 19
 
< 0.1%
17 17
 
< 0.1%
11 16
 
< 0.1%
Other values (771) 1821
 
2.1%
ValueCountFrequency (%)
0 83048
97.6%
1 74
 
0.1%
2 24
 
< 0.1%
3 24
 
< 0.1%
4 20
 
< 0.1%
5 19
 
< 0.1%
6 16
 
< 0.1%
7 13
 
< 0.1%
8 21
 
< 0.1%
9 15
 
< 0.1%
ValueCountFrequency (%)
19159 1
< 0.1%
10996 1
< 0.1%
10995 1
< 0.1%
10994 1
< 0.1%
10993 1
< 0.1%
10985 1
< 0.1%
10980 1
< 0.1%
10012 1
< 0.1%
9982 1
< 0.1%
9863 1
< 0.1%

Median playtime forever
Real number (ℝ)

SKEWED  ZEROS 

Distinct1896
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.316029
Minimum0
Maximum208473
Zeros70192
Zeros (%)82.5%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:21.577809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile332
Maximum208473
Range208473
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1510.7321
Coefficient of variation (CV)16.189417
Kurtosis8043.2472
Mean93.316029
Median Absolute Deviation (MAD)0
Skewness79.548322
Sum7941474
Variance2282311.5
MonotonicityNot monotonic
2024-09-14T16:51:21.882745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 70192
82.5%
1 334
 
0.4%
2 130
 
0.2%
3 103
 
0.1%
4 101
 
0.1%
6 97
 
0.1%
11 96
 
0.1%
5 95
 
0.1%
8 86
 
0.1%
9 83
 
0.1%
Other values (1886) 13786
 
16.2%
ValueCountFrequency (%)
0 70192
82.5%
1 334
 
0.4%
2 130
 
0.2%
3 103
 
0.1%
4 101
 
0.1%
5 95
 
0.1%
6 97
 
0.1%
7 80
 
0.1%
8 86
 
0.1%
9 83
 
0.1%
ValueCountFrequency (%)
208473 1
< 0.1%
145727 1
< 0.1%
136629 1
< 0.1%
136291 1
< 0.1%
114016 1
< 0.1%
102435 1
< 0.1%
99108 1
< 0.1%
90351 1
< 0.1%
76068 1
< 0.1%
65792 1
< 0.1%

Median playtime two weeks
Real number (ℝ)

SKEWED  ZEROS 

Distinct784
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.467328
Minimum0
Maximum19159
Zeros83048
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size1.3 MiB
2024-09-14T16:51:22.176044image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum19159
Range19159
Interquartile range (IQR)0

Descriptive statistics

Standard deviation205.37294
Coefficient of variation (CV)17.909399
Kurtosis2307.8499
Mean11.467328
Median Absolute Deviation (MAD)0
Skewness41.805559
Sum975904
Variance42178.046
MonotonicityNot monotonic
2024-09-14T16:51:22.491698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 83048
97.6%
1 74
 
0.1%
3 25
 
< 0.1%
2 23
 
< 0.1%
8 20
 
< 0.1%
10 19
 
< 0.1%
5 19
 
< 0.1%
4 18
 
< 0.1%
6 17
 
< 0.1%
23 17
 
< 0.1%
Other values (774) 1823
 
2.1%
ValueCountFrequency (%)
0 83048
97.6%
1 74
 
0.1%
2 23
 
< 0.1%
3 25
 
< 0.1%
4 18
 
< 0.1%
5 19
 
< 0.1%
6 17
 
< 0.1%
7 13
 
< 0.1%
8 20
 
< 0.1%
9 14
 
< 0.1%
ValueCountFrequency (%)
19159 1
< 0.1%
10996 1
< 0.1%
10995 2
< 0.1%
10994 2
< 0.1%
10993 1
< 0.1%
10985 1
< 0.1%
10980 1
< 0.1%
10012 1
< 0.1%
9982 1
< 0.1%
9863 1
< 0.1%

Developers
Text

MISSING 

Distinct49870
Distinct (%)61.2%
Missing3587
Missing (%)4.2%
Memory size1.3 MiB
2024-09-14T16:51:23.125624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length584
Median length254
Mean length14.520965
Min length1

Characters and Unicode

Total characters1183691
Distinct characters2293
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38793 ?
Unique (%)47.6%

Sample

1st rowPerpetual FX Creative
2nd rowRusty Moyher
3rd rowCampião Games
4th rowOdd Critter Games
5th rowUnusual Games
ValueCountFrequency (%)
games 13332
 
8.0%
studio 4868
 
2.9%
studios 4476
 
2.7%
game 1682
 
1.0%
ltd 1671
 
1.0%
inc 1637
 
1.0%
llc 1489
 
0.9%
entertainment 1476
 
0.9%
interactive 1337
 
0.8%
software 1304
 
0.8%
Other values (47644) 133378
80.0%
2024-09-14T16:51:24.147870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 99727
 
8.4%
a 87926
 
7.4%
85187
 
7.2%
i 70132
 
5.9%
o 69219
 
5.8%
t 60320
 
5.1%
n 55036
 
4.6%
r 54006
 
4.6%
s 52511
 
4.4%
m 38655
 
3.3%
Other values (2283) 510972
43.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1183691
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 99727
 
8.4%
a 87926
 
7.4%
85187
 
7.2%
i 70132
 
5.9%
o 69219
 
5.8%
t 60320
 
5.1%
n 55036
 
4.6%
r 54006
 
4.6%
s 52511
 
4.4%
m 38655
 
3.3%
Other values (2283) 510972
43.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1183691
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 99727
 
8.4%
a 87926
 
7.4%
85187
 
7.2%
i 70132
 
5.9%
o 69219
 
5.8%
t 60320
 
5.1%
n 55036
 
4.6%
r 54006
 
4.6%
s 52511
 
4.4%
m 38655
 
3.3%
Other values (2283) 510972
43.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1183691
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 99727
 
8.4%
a 87926
 
7.4%
85187
 
7.2%
i 70132
 
5.9%
o 69219
 
5.8%
t 60320
 
5.1%
n 55036
 
4.6%
r 54006
 
4.6%
s 52511
 
4.4%
m 38655
 
3.3%
Other values (2283) 510972
43.2%

Publishers
Text

MISSING 

Distinct43366
Distinct (%)53.4%
Missing3867
Missing (%)4.5%
Memory size1.3 MiB
2024-09-14T16:51:24.662051image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length164
Median length84
Mean length13.908994
Min length1

Characters and Unicode

Total characters1129911
Distinct characters2045
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33497 ?
Unique (%)41.2%

Sample

1st rowPerpetual FX Creative
2nd rowWild Rooster
3rd rowCampião Games
4th rowOdd Critter Games
5th rowUnusual Games
ValueCountFrequency (%)
games 14635
 
9.0%
studio 4307
 
2.6%
studios 4289
 
2.6%
entertainment 2153
 
1.3%
ltd 2019
 
1.2%
llc 1794
 
1.1%
inc 1746
 
1.1%
game 1593
 
1.0%
interactive 1501
 
0.9%
software 1012
 
0.6%
Other values (39161) 128439
78.6%
2024-09-14T16:51:25.542577image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 95491
 
8.5%
a 82554
 
7.3%
82293
 
7.3%
i 68254
 
6.0%
o 63460
 
5.6%
t 59513
 
5.3%
s 52321
 
4.6%
n 51858
 
4.6%
r 50656
 
4.5%
m 38584
 
3.4%
Other values (2035) 484927
42.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1129911
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 95491
 
8.5%
a 82554
 
7.3%
82293
 
7.3%
i 68254
 
6.0%
o 63460
 
5.6%
t 59513
 
5.3%
s 52321
 
4.6%
n 51858
 
4.6%
r 50656
 
4.5%
m 38584
 
3.4%
Other values (2035) 484927
42.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1129911
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 95491
 
8.5%
a 82554
 
7.3%
82293
 
7.3%
i 68254
 
6.0%
o 63460
 
5.6%
t 59513
 
5.3%
s 52321
 
4.6%
n 51858
 
4.6%
r 50656
 
4.5%
m 38584
 
3.4%
Other values (2035) 484927
42.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1129911
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 95491
 
8.5%
a 82554
 
7.3%
82293
 
7.3%
i 68254
 
6.0%
o 63460
 
5.6%
t 59513
 
5.3%
s 52321
 
4.6%
n 51858
 
4.6%
r 50656
 
4.5%
m 38584
 
3.4%
Other values (2035) 484927
42.9%

Categories
Text

MISSING 

Distinct5648
Distinct (%)7.0%
Missing4598
Missing (%)5.4%
Memory size1.3 MiB
2024-09-14T16:51:26.013018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length371
Median length346
Mean length50.972051
Min length3

Characters and Unicode

Total characters4103505
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3602 ?
Unique (%)4.5%

Sample

1st rowSingle-player,Multi-player,Steam Achievements,Partial Controller Support
2nd rowSingle-player,Steam Achievements,Full controller support,Steam Leaderboards,Remote Play on Phone,Remote Play on Tablet,Remote Play on TV
3rd rowSingle-player
4th rowSingle-player,Full controller support
5th rowSingle-player,Steam Achievements
ValueCountFrequency (%)
single-player,steam 32581
 
11.3%
controller 26924
 
9.4%
single-player 23990
 
8.3%
support,steam 12109
 
4.2%
cloud 12043
 
4.2%
achievements,full 11371
 
4.0%
support 11021
 
3.8%
achievements,steam 10588
 
3.7%
play 10140
 
3.5%
trading 9889
 
3.4%
Other values (397) 126684
44.1%
2024-09-14T16:51:26.843011image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 493819
 
12.0%
l 351742
 
8.6%
r 263076
 
6.4%
a 262094
 
6.4%
t 237453
 
5.8%
206835
 
5.0%
S 204562
 
5.0%
n 197645
 
4.8%
p 185592
 
4.5%
i 181126
 
4.4%
Other values (36) 1519561
37.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4103505
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 493819
 
12.0%
l 351742
 
8.6%
r 263076
 
6.4%
a 262094
 
6.4%
t 237453
 
5.8%
206835
 
5.0%
S 204562
 
5.0%
n 197645
 
4.8%
p 185592
 
4.5%
i 181126
 
4.4%
Other values (36) 1519561
37.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4103505
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 493819
 
12.0%
l 351742
 
8.6%
r 263076
 
6.4%
a 262094
 
6.4%
t 237453
 
5.8%
206835
 
5.0%
S 204562
 
5.0%
n 197645
 
4.8%
p 185592
 
4.5%
i 181126
 
4.4%
Other values (36) 1519561
37.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4103505
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 493819
 
12.0%
l 351742
 
8.6%
r 263076
 
6.4%
a 262094
 
6.4%
t 237453
 
5.8%
206835
 
5.0%
S 204562
 
5.0%
n 197645
 
4.8%
p 185592
 
4.5%
i 181126
 
4.4%
Other values (36) 1519561
37.0%

Genres
Text

MISSING 

Distinct2471
Distinct (%)3.0%
Missing3555
Missing (%)4.2%
Memory size1.3 MiB
2024-09-14T16:51:27.225446image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length236
Median length133
Mean length22.127545
Min length3

Characters and Unicode

Total characters1804457
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1085 ?
Unique (%)1.3%

Sample

1st rowCasual,Indie,Sports
2nd rowAction,Indie
3rd rowAction,Adventure,Indie,Strategy
4th rowAdventure,Casual,Indie
5th rowAdventure,Indie
ValueCountFrequency (%)
access 10402
 
9.4%
to 6631
 
6.0%
casual,indie 4811
 
4.4%
action,indie 4421
 
4.0%
action,adventure,indie 3643
 
3.3%
adventure,indie 3110
 
2.8%
adventure,casual,indie 2561
 
2.3%
indie 2547
 
2.3%
action,casual,indie 2529
 
2.3%
casual 2486
 
2.2%
Other values (1473) 67371
61.0%
2024-09-14T16:51:27.933378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 167836
 
9.3%
, 151584
 
8.4%
n 146259
 
8.1%
i 138234
 
7.7%
t 130819
 
7.2%
a 126730
 
7.0%
d 90440
 
5.0%
u 85943
 
4.8%
l 77168
 
4.3%
A 76305
 
4.2%
Other values (34) 613139
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1804457
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 167836
 
9.3%
, 151584
 
8.4%
n 146259
 
8.1%
i 138234
 
7.7%
t 130819
 
7.2%
a 126730
 
7.0%
d 90440
 
5.0%
u 85943
 
4.8%
l 77168
 
4.3%
A 76305
 
4.2%
Other values (34) 613139
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1804457
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 167836
 
9.3%
, 151584
 
8.4%
n 146259
 
8.1%
i 138234
 
7.7%
t 130819
 
7.2%
a 126730
 
7.0%
d 90440
 
5.0%
u 85943
 
4.8%
l 77168
 
4.3%
A 76305
 
4.2%
Other values (34) 613139
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1804457
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 167836
 
9.3%
, 151584
 
8.4%
n 146259
 
8.1%
i 138234
 
7.7%
t 130819
 
7.2%
a 126730
 
7.0%
d 90440
 
5.0%
u 85943
 
4.8%
l 77168
 
4.3%
A 76305
 
4.2%
Other values (34) 613139
34.0%

Tags
Text

MISSING 

Distinct57101
Distinct (%)89.2%
Missing21100
Missing (%)24.8%
Memory size1.3 MiB
2024-09-14T16:51:28.428648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length288
Median length207
Mean length125.08132
Min length2

Characters and Unicode

Total characters8005580
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55719 ?
Unique (%)87.1%

Sample

1st rowIndie,Casual,Sports,Bowling
2nd rowIndie,Action,Pixel Graphics,2D,Retro,Arcade,Score Attack,Minimalist,Comedy,Singleplayer,Fast-Paced,Casual,Funny,Parody,Difficult,Gore,Violent,Western,Controller,Blood
3rd row2D Platformer,Atmospheric,Surreal,Mystery,Puzzle,Survival,Adventure,Linear,Singleplayer,Experimental,Platformer,Precision Platformer,Puzzle-Platformer,2D,Stylized,Physics,Time Manipulation,Casual,Indie
4th rowIndie,Adventure,Nudity,Violent,Sexual Content,Story Rich
5th rowTurn-Based Combat,Massively Multiplayer,Multiplayer,RPG,Tactical RPG,Exploration,PvP,MMORPG,Turn-Based Strategy,God Game,Strategy,2.5D,Magic,Medieval,Mythology,Class-Based,Turn-Based Tactics,Singleplayer,Online Co-Op,Co-op
ValueCountFrequency (%)
4875
 
1.7%
to 4082
 
1.4%
em 3550
 
1.2%
early 2495
 
0.9%
free 2082
 
0.7%
and 1987
 
0.7%
your 1960
 
0.7%
own 1960
 
0.7%
only 1404
 
0.5%
action 1216
 
0.4%
Other values (147297) 261028
91.1%
2024-09-14T16:51:29.352143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 746226
 
9.3%
e 639885
 
8.0%
i 522082
 
6.5%
a 500616
 
6.3%
r 496515
 
6.2%
t 465937
 
5.8%
o 457290
 
5.7%
l 432430
 
5.4%
n 419871
 
5.2%
c 240692
 
3.0%
Other values (60) 3084036
38.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8005580
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 746226
 
9.3%
e 639885
 
8.0%
i 522082
 
6.5%
a 500616
 
6.3%
r 496515
 
6.2%
t 465937
 
5.8%
o 457290
 
5.7%
l 432430
 
5.4%
n 419871
 
5.2%
c 240692
 
3.0%
Other values (60) 3084036
38.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8005580
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 746226
 
9.3%
e 639885
 
8.0%
i 522082
 
6.5%
a 500616
 
6.3%
r 496515
 
6.2%
t 465937
 
5.8%
o 457290
 
5.7%
l 432430
 
5.4%
n 419871
 
5.2%
c 240692
 
3.0%
Other values (60) 3084036
38.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8005580
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 746226
 
9.3%
e 639885
 
8.0%
i 522082
 
6.5%
a 500616
 
6.3%
r 496515
 
6.2%
t 465937
 
5.8%
o 457290
 
5.7%
l 432430
 
5.4%
n 419871
 
5.2%
c 240692
 
3.0%
Other values (60) 3084036
38.5%

Interactions

2024-09-14T16:50:51.244440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:52.468162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:56.487465image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:01.374882image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:05.210839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:09.291045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:14.178252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:18.464356image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:22.420129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:27.363305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:33.235196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:37.614509image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:42.281629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:46.464128image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:51.676468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:52.763266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:56.893040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:01.644108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:05.450064image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:09.672506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:14.460949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:18.744183image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:22.669086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:27.619813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:33.512946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:37.930967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:42.554637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:46.716254image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:52.073782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:53.020258image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:57.204553image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:01.914573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:05.709052image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:10.024410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:14.723378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:19.012597image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:23.049857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:27.891802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:33.800851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:38.322780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:42.831995image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:47.564143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:52.514953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:53.270087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:57.579331image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:02.167092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:05.981909image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:10.433345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:15.003718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:19.289436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:23.426793image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:28.186079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:34.088495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:38.731746image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:43.124968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:47.828017image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:52.901227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:53.533528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:57.940343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:02.420399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:06.236197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:10.754437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:15.250047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:19.545989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:23.819412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:28.642935image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:34.372291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:39.090936image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:43.393110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:48.088799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:53.298134image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:53.796187image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:58.308914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:02.687950image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:06.491712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:11.151270image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:15.530866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:19.833440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:24.160748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:29.229838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:34.648476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:39.528179image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:43.682141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:48.362405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:53.701479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:54.058020image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:58.711331image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:02.991851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:06.749310image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:11.527138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:15.790311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:20.111764image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:24.564482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:29.763941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:34.926984image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:39.983603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:44.010738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:48.629570image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:53.985464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:54.317496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:59.133405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:03.257059image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:07.387254image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:11.929382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:16.066806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:20.385917image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:24.921803image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:30.278278image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:35.203718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:40.270907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:44.321066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:48.918817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:54.238928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:54.587289image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:59.687985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:03.515623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:07.622765image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:12.359851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:16.326323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:20.677669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:25.277756image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:30.914729image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:35.480268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:40.539881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:44.598568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:49.190881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:54.512126image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:54.842089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:59.964810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:03.787981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:07.883683image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:12.716780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:16.597619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:20.997082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:25.688790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:31.354081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:35.751015image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:40.846987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:44.933349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:49.455759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:54.802104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:55.127211image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:00.239697image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:04.080941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:08.162440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:12.996254image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:16.899773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:21.285820image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:26.156870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:32.095607image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:36.070929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:41.141340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:45.262535image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:49.745688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:55.089133image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:55.412457image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:00.526357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:04.373108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:08.445799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:13.269334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:17.169450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:21.566178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:26.500617image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:32.398887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:36.368862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:41.421809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:45.557980image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:50.061054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:55.387346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:55.715646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:00.832556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:04.654030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:08.729176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:13.596589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:17.896049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:21.883035image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:26.787681image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:32.688197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:36.818031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:41.708690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:45.895284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:50.509165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:55.670375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:49:56.051862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:01.095195image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:04.925030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:08.999066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:13.882265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:18.169485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:22.128558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:27.074092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:32.952356image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:37.170904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:41.992766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:46.175464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-09-14T16:50:50.871592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Missing values

2024-09-14T16:50:56.255311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-14T16:50:57.460555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-09-14T16:50:58.714848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

NameRelease dateEstimated ownersPeak CCURequired agePriceDLC countAbout the gameSupported languagesFull audio languagesReviewsWindowsMacLinuxMetacritic scoreUser scorePositiveNegativeScore rankAchievementsRecommendationsNotesAverage playtime foreverAverage playtime two weeksMedian playtime foreverMedian playtime two weeksDevelopersPublishersCategoriesGenresTags
0Galactic BowlingOct 21, 20080 - 200000019.990Galactic Bowling is an exaggerated and stylized bowling game with an intergalactic twist. Players will engage in fast-paced single and multi-player competition while being submerged in a unique new universe filled with over-the-top humor, wild characters, unique levels, and addictive game play. The title is aimed at players of all ages and skill sets. Through accessible and intuitive controls and game-play, Galactic Bowling allows you to jump right into the action. A single-player campaign and online play allow you to work your way up the ranks of the Galactic Bowling League! Whether you have hours to play or only a few minutes, Galactic Bowling is a fast paced and entertaining experience that will leave you wanting more! Full Single-player story campaign including 11 Characters and Environments. 2 Single-player play modes including Regular and Battle Modes. Head to Head Online Multiplayer play Modes. Super Powers, Special Balls, and Whammies. Unlockable Characters, Environments, and Minigames. Unlock all 30 Steam Achievements!['English'][]NaNTrueFalseFalse00611NaN300NaN0000Perpetual FX CreativePerpetual FX CreativeSingle-player,Multi-player,Steam Achievements,Partial Controller SupportCasual,Indie,SportsIndie,Casual,Sports,Bowling
1Train BanditOct 12, 20170 - 20000000.990THE LAW!! Looks to be a showdown atop a train. This will be your last fight. Good luck, Train Bandit. WHAT IS THIS GAME? Train Bandit is a simple score attack game. The Law will attack you from both sides. Your weapon is your keyboard. You'll use those keys to kick the living shit out of the law. React quickly by attacking the correct direction. React...or you're dead. THE FEATURES Unlock new bandits Earn Achievements Become Steam's Most Wanted ? Battle elite officers Kick the law's ass['English', 'French', 'Italian', 'German', 'Spanish - Spain', 'Japanese', 'Portuguese - Brazil', 'Russian', 'Simplified Chinese', 'Traditional Chinese'][]NaNTrueTrueFalse00535NaN120NaN0000Rusty MoyherWild RoosterSingle-player,Steam Achievements,Full controller support,Steam Leaderboards,Remote Play on Phone,Remote Play on Tablet,Remote Play on TVAction,IndieIndie,Action,Pixel Graphics,2D,Retro,Arcade,Score Attack,Minimalist,Comedy,Singleplayer,Fast-Paced,Casual,Funny,Parody,Difficult,Gore,Violent,Western,Controller,Blood
2Jolt ProjectNov 17, 20210 - 20000004.990Jolt Project: The army now has a new robotics project, jolt. It's up to you to control it and ensure the success of the missions! There are 9 stages of taking the breath away with the right difficulty and good gameplay. Plus an insane way of survival! Fire missiles at cars, tanks, helicopters and turrets! The fun is guaranteed! Use your mouse to aim and shoot and take out the enemies! In this game you will have to be aware of the various enemies who will do everything to destroy your charges and prevent the success of your mission! Cartoon-style graphics are optimized and fun and generate an excellent gaming environment!['English', 'Portuguese - Brazil'][]NaNTrueFalseFalse0000NaN00NaN0000Campião GamesCampião GamesSingle-playerAction,Adventure,Indie,StrategyNaN
3Henosis™Jul 23, 20200 - 20000005.990HENOSIS™ is a mysterious 2D Platform Puzzler where players are propelled into weird and visceral worlds as they take control of a small, droplet of water while overcoming obstacles and enemies throughout each level. The Player must venture through each world as it collects precious water tokens in order open the exit portal and restore vitality to its drought-ridden home world. Features: Traverse your way through 27 hand-crafted levels Unique player mechanics Battle menacing bosses across 3 distinct worlds* Original artwork &amp; animation Full controller support Localization support * Hidden world included!['English', 'French', 'Italian', 'German', 'Spanish - Spain', 'Japanese', 'Korean', 'Portuguese', 'Russian', 'Simplified Chinese', 'Traditional Chinese'][]NaNTrueTrueTrue0030NaN00NaN0000Odd Critter GamesOdd Critter GamesSingle-player,Full controller supportAdventure,Casual,Indie2D Platformer,Atmospheric,Surreal,Mystery,Puzzle,Survival,Adventure,Linear,Singleplayer,Experimental,Platformer,Precision Platformer,Puzzle-Platformer,2D,Stylized,Physics,Time Manipulation,Casual,Indie
4Two Weeks in PainlandFeb 3, 20200 - 20000000.000ABOUT THE GAME Play as a hacker who has arranged a deal with a gangster. That’s how the protagonist, Jack, is assigned a mission that should be accomplished in a specific timeframe, which he will find out soon enough. THE GAME’S FEATURES Spy on 4 senior managers within an organization to find out about their personalities. Manage the recruitment process in the organization to improve the work climate. Hack the candidates who want to get into the organization to make your job easier. Try to avoid having your physical health impacted negatively in the process. All of this while you enjoy an interesting story full of humor and action that evolves along with the game.['English', 'Spanish - Spain'][]NaNTrueTrueFalse00508NaN170This Game may contain content not appropriate for all ages, or may not be appropriate for viewing at work: violence, general Mature Content.0000Unusual GamesUnusual GamesSingle-player,Steam AchievementsAdventure,IndieIndie,Adventure,Nudity,Violent,Sexual Content,Story Rich
5Wartune RebornFeb 26, 202150000 - 1000006800.000Feel tired of auto-fight? Feel tired of boring numerical combinations? Let us try this amazing and exciting game! Right! Wartune Reborn is the super popular magic epic game as we know. Now, the magnificent magic epic game restarts, reminds you the classical plays and brings great experience. In Cloud City, you are going to maintains the Wartune movement, fighting the abyss monsters to protect the world from chaos. Don't be nervous! With protection of Dinah, Priestess of Light, you will have the power to absorb the chord, incorporate those forces without kings into your own ones, and make contract with and train apotheosis of Sylphs. You can improve yourself in a series of RPG adventures including instances battles, wild fighting, occupation and plunder. At the same time, you can run your own ligeance and castles and ally yourself with other players in the world who attack the Chaos. All of you are going to cooperate to protect the world from the control and destroy of Redoga Drake and bring the brightness back to Cloud City...... Enter Wartune Reborn to enjoy thinking of battles and playing the game! 1. RPG simulation, S- semi TBS battle, castles constructions, occupation &amp; expelling make you the best lords 2. Magical epic plots and original prominent symphony show the ancient and magnificent medieval chapter. 3. Military organization, runes and strategies contribute to super power. 4. Sylph awakening, skills and training, you will cooperate to beat BOSS. 5. Explore the magical world of the wild, jungles, deserts and snow mountains freely in the map of the vast outer city, to find mysterious ancient treasure. 6. Avatar system provides cool fashion, wings, mounts, weapon appearance with arbitrary combination. Wartune Reborn, Magical epic, Expect Heroes! Classical playing brings you amazing experience!['English'][]NaNTrueFalseFalse008749NaN00NaN00007Road7RoadSingle-player,Multi-player,MMO,PvP,Online PvP,Co-op,Online Co-op,In-App PurchasesAdventure,Casual,Free to Play,Massively Multiplayer,RPG,StrategyTurn-Based Combat,Massively Multiplayer,Multiplayer,RPG,Tactical RPG,Exploration,PvP,MMORPG,Turn-Based Strategy,God Game,Strategy,2.5D,Magic,Medieval,Mythology,Class-Based,Turn-Based Tactics,Singleplayer,Online Co-Op,Co-op
6TD WorldsJan 9, 20220 - 200003010.991TD Worlds is a dynamic, highly strategical game that challenges your skill. Build an impenetrable defense and get ready to plunge into a new, unknown world to uncover its secrets. In this bizarre universe, each attempt will be unique in its own way, which provides many hours of fun to play. Clear three completely different worlds from darkness, spread your influence everywhere. unique conditions in each game; losing is an important part of game progress. Each defeat reveals something new for you; dynamic storytelling: the more you play, the more you learn about the world; get random rewards after each level; tired of playing? Feel free to leave the game, next time you will continue where you left; experiment with different tactics; Twitch integration - play with your viewers.['English', 'Russian', 'Danish'][]NaNTrueFalseFalse00217NaN620NaN0000MAKSIM VOLKAUMAKSIM VOLKAUSingle-player,Steam Achievements,Steam CloudIndie,StrategyTower Defense,Rogue-lite,RTS,Replay Value,Perma Death,2D,Isometric,Difficult,Rogue-like,Dynamic Narration,Stylized,Real Time Tactics,Strategy,Minimalist,Abstract,Tactical,Atmospheric,Singleplayer,Sci-fi,Mystery
7Legend of Rome - The Wrath of MarsMay 5, 20220 - 20000209.990When the Roman people honored a simple warrior for the victories in battle they angered the god of war. Mars, infuriated, sends his army and brings great destruction to the Roman people. Experience a challenging match 3 game and help the Roman people appease Mars, the god of war! Build and restore the proud city to its original splendor. In Legend of Rome play through an exciting story, earn bonuses, power ups and trophies, solve mini-games and extra levels to get closer to your goal. - Varied match 3 game with many extras. - Play through a challenging story. - Build and restore the city. - Earn different bonuses, upgrades and extras. - Solve challenging mini-games and bonus levels.['English', 'German']['English', 'German']NaNTrueFalseFalse0000NaN00NaN0000magnussoftmagnussoftSingle-player,Steam CloudCasualNaN
8MazM: Jekyll and HydeApr 2, 20200 - 200001014.990'MazM: Jekyll and Hyde' is a darkly entertaining adventure game based on the classic 1886 novel 'The Strange Case of Dr. Jekyll and Mr. Hyde' by Robert Louis Stevenson, in which you'll tackle the mystery from a totally new angle! You'll travel back to 19th century London and view the city through the eyes of Mr. Utterson, a lawyer that walks the true path hunting for clues to solve a disturbing mystery, and Mr. Hyde, who has been pushed to his physical limits. Wander the streets of this psychological thriller and prepare for an ending you would never expect! The version of London presented in 'MazM: Jekyll and Hyde' has a dark, heavy atmosphere, creating a sense of the eerie and macabre. The stunning artwork and unsettling music help to further intensify the disturbing nature of the game. Travel throughout London searching for clues, and allow the world of this classic novel to envelop you as you experience the tale of one man's many challenges and potential downfall!['English', 'French', 'Italian', 'German', 'Spanish - Spain', 'Russian', 'Japanese', 'Simplified Chinese', 'Traditional Chinese', 'Korean'][]NaNTrueFalseFalse00766NaN250NaN0000Growing SeedsCFK Co., Ltd.Single-player,Steam Achievements,Full controller supportAdventure,RPG,Simulation,StrategyAdventure,Simulation,RPG,Strategy,Singleplayer,Classic
9Deadlings: Rotten EditionNov 11, 201450000 - 100000003.990Death is lonely. He has zero friends on his FaceTome account and no one to hang out with. So, in order to feel better he begins “Project Deadlings”. Death buys a factory where he can build his laboratory and begin training a massive army of zombie minions. As the army of Deadlings grows, the mazes of the laboratory become deadlier, loaded with puzzles and death-defying traps. Different Deadlings have their own unique abilities: Bonesack is agile - he can run and jump, Creep can climb on walls and ceilings, Lazybrain treads slowly but carefully and Stencher... well Stencher has gastric problems so he can use his powerful gas clouds to fly. You will have to combine all of these abilities to find your way in Death's Maze. Can you help Death to kill his boredom? Will you be able to navigate all 60+ levels available in Deadlings? Will you complete Project Deadlings, and successfully train all of your zombie minions? Arcade side-scroller with strategy elements! Four different types of zombie minions with unique abilities! 70 levels of pure zombie gore fun! Additional game mode - Nightmare - only for the hardcore gamers! What's new in the Rotten Edition? 10 brand new bonus levels 15 new levels in Nightmare Mode Steam achievements and leaderboards Full controller support Nightmare mode unlocked from the beginning Steam Trading Cards and Badges HD graphics['English', 'Polish', 'French', 'Italian', 'German', 'Spanish - Spain', 'Portuguese', 'Russian', 'Japanese']['English', 'Japanese']NaNTrueTrueTrue0022545NaN320NaN70307820ONE MORE LEVELONE MORE LEVELSingle-player,Steam Achievements,Steam Trading Cards,Partial Controller Support,Steam CloudAction,Adventure,IndieAction,Indie,Adventure,Puzzle-Platformer,Arcade,Zombies
NameRelease dateEstimated ownersPeak CCURequired agePriceDLC countAbout the gameSupported languagesFull audio languagesReviewsWindowsMacLinuxMetacritic scoreUser scorePositiveNegativeScore rankAchievementsRecommendationsNotesAverage playtime foreverAverage playtime two weeksMedian playtime foreverMedian playtime two weeksDevelopersPublishersCategoriesGenresTags
8485Dense forestJan 4, 20240 - 0005.990In this game, you have a fairly simple task - to collect all the fruits to complete the level. The task is complicated by the fact that the main character wants to stop the fabulous creatures, they will do everything to stop the main character. You will get points for picking fruits. The levels are a kind of maze in which you need to be careful in order not to get caught by enemies. Special fruits will help you get out of the most critical situations, which make enemies vulnerable for a while. Thus, it is possible to get out of seemingly hopeless situations. By building the path correctly, you will achieve your goal! Go ahead, Hero! Your destiny awaits you! -Beautiful graphics -Interesting gameplay -Dangerous enemies['English'][]NaNTrueFalseFalse0000NaN50NaN0000GamesforgamesGamesforgamesSingle-player,Steam AchievementsAction,Adventure,Casual,RPG,Simulation,Sports,StrategyNaN
8486Cats VS GhostsJan 2, 20240 - 20000000.990Tower Defense: Cats are towers, ghosts are enemies and humans are target. You must put the correct cat to destroy the ghosts. History: Few months ago, something strange began to happen. Civilians reported seeing strange figures wandering the streets, causing chaos and destruction in their wake. Soon it was discovered that they were ghosts who had appeared in the town and seemed to have no friendly intentions. As the days went by, the ghosts became more and more aggressive, and the humans began to feel helpless in their presence. But there was a group of beings who wouldn't give up so easily: the cats. The cats, known for their cunning and bravery, began patrolling the streets at night, searching for any signs of the ghosts. When they found one, they pounced on it without fear, clawing, biting and shooting until it disappeared. The humans couldn't believe what they were seeing. The cats, who normally kept their distance from them, were now protecting them from a supernatural threat. No one knows for sure why the cats decided to defend humans against the ghosts, but some speculate that they did it out of love for their home and their slaves. Since then, it's said that the cats are always vigilant, ready to protect their humans from any supernatural danger that may arise.['English'][]NaNTrueFalseFalse0010NaN00NaN0000Ruben Dario AcostaRuben Dario AcostaSingle-playerCasual,IndieCasual,Tower Defense,Time Management,3D,Cartoon,Cartoony,Colorful,Alternate History,Comedy,Demons,Funny,Management,Mystery,Base-Building,Bullet Time,Singleplayer,Cats,Indie
8487Scorching Engines PlaytestJan 6, 20240 - 0000.000NaN[][]NaNTrueFalseFalse0000NaN00NaN0000NaNNaNNaNNaNNaN
8488Fallen's ChallengeJan 3, 20240 - 20000004.990You have fallen into Hell and made an unlikely friend. He promises to help you escape if you collect the scattered skulls found in this dimension. Each level will give you a randomized theme or layout, giving you a fresh playthrough every time! The dungeons are filled with traps and monsters to help make your journey more difficult. With the power of Telekinesis you can move blocks to create bridges for you to walk on. With the powers of the Gems you find, you'll gain abilities to help you traverse the different elements and also the ability to use the different elements to defend yourself!['English']['English']NaNTrueFalseFalse0000NaN00NaN0000Electronic Overthrow LLCElectronic Overthrow LLCSingle-player,Partial Controller SupportAction,Adventure,Casual,Indie,Strategy,Early AccessNaN
8489Lost in the Void : Chapter OneJan 6, 20240 - 20000004.992Immerse yourself in the mesmerizing realm of Lost in the Void —an enchanting isometric pixel art adventure skillfully interwoven with captivating RPG elements. Drawing inspiration from the cherished era of the 80s, this game is meticulously crafted to rekindle the enchantment of your childhood dreams. Lost in the Void unfolds as an episodic journey, akin to your beloved TV shows, with each episode released one at a time, promising a continuous tapestry of immersive storytelling and thrilling gameplay. Embark on a Journey as a High School Senior Embark on a transformative journey as a high school senior in Lost in the Void. Amidst the bustling corridors of academia and the camaraderie of your tight-knit group of friends, an eerie voice begins to resonate within your mind. It beckons you toward an enigmatic and shadowy path, compelling you to confront a pivotal decision. Will you succumb to the allure of this mysterious force, or will you resist its persuasive influence, shaping your destiny in the process? Forge Unforgettable Bonds with Your Companions Throughout your enthralling expedition, you'll be accompanied by Martin, Sasha, and Aaron – your steadfast friends, each with their own distinct personalities that react dynamically to your choices. Depending on your decisions, their affections for you may blossom or wither away. Shape Your Character through Skill Distribution At the onset of the game, indulge in character creation where you allocate points into three primary skills – Fight, Tech, or Comms. These skill allocations will dictate how you navigate intricate dialogues, as combat is non-existent in this enthralling adventure. All in-game situations are resolved through a robust dialogue system, putting the power of choice firmly in your hands. Unleash Your Imagination in a Narrative-Driven Experience Lost in the Void is an episodic captivating narrative-driven game that captures the essence of classic pen-and-paper RPG games and game-books. While our pixel art style sets the stage, the game's rich narration vividly paints a detailed picture of your surroundings, allowing your imagination to breathe life into every nook and cranny of this mesmerizing universe.['English', 'Slovak'][]NaNTrueFalseFalse0000NaN170Alcohol, Vulgarism (Harsh Language)0000NightcallNightcallSingle-player,Steam Achievements,Full controller supportAdventure,Indie,RPG,Free to PlayNaN
8490Mannerheim's Saloon CarJan 2, 20240 - 0000.000Marshal Mannerheim’s Saloon Car is the train carriage that was used by Carl Gustaf Emil Mannerheim and his personnel in 1939-1946. Mannerheim was the commander-in-chief of Finland’s defense forces during World War II, and later he became the president of Finland. During the winter war between Finland and Soviet Union, Mannerheim traveled nearly 79 000 kilometers with the train. This historical train carriage is currently located in Mikkeli, Finland, where it can be visited once a year on June 4th. This application allows its user to visit Mannerheim’s Saloon Car in VR and to explore old items, documents, photo albums, film clips, and even listen to historical radio broadcasts. It is possible to choose from two languages: English or Finnish. The app was developed by Xamk Game Studios at South-Eastern Finland University of Applied Sciences in the ARMikkeli project. The project was partially funded by the South Savo Regional Council from the European Regional Development Fund.['English', 'Finnish']['Finnish']NaNTrueFalseFalse0000NaN00NaN0000Xamk Game StudiosSodan ja rauhan keskus Muisti, PäämajamuseoSingle-player,Tracked Controller Support,VR OnlyAdventure,SimulationNaN
8491Beer RunJan 3, 20240 - 0000.000Beer Run is an Indie game created to steal beers from supermarkets. Three guys with a plan to steal more beer after running out, they go into multiple grocery stores to rob beer. Security guards are the enemy while the characters intend to rob from a store. As you progress throughout the game, each level gets harder by improving their security system. Multiple security guards in certain levels that make it tough to steal without being caught. As you collect more beers the character starts to slow down from all the weight being carried, creating another challenge besides evading the security. Features include - Limited carrying supply Slowed down speed when carrying beers. Can drop beers to gain speed. 3-star reward system Story 3 different characters['English'][]NaNTrueFalseFalse0000NaN00NaN0000955 Games955 GamesSingle-playerCasual,IndieNaN
8492My Friend The SpiderJan 4, 20240 - 0000.000A small 'horror' narrative game about isolation and depression. My Friend The Spider is a 10-15 minute walking simulator where the player finds themselves voluntarily locked in a room to escape and isolate due to their current emotional state and befriending a spider that grows in size with the story's progression. I originally worked on the game for a month and a half around October 2022. My idea was to experiment with the Unity engine in order to practice my coding and get used to the engine. I had a short story in mind based on personal experiences and thought it would be a good idea to flesh it out as a narrative 'game' instead. Everything bar the art assets was done by me. My wife helped with the voice acting (and emotional support). After releasing it, it got quite a few number of views and plays - seeing people's comments about how they were moved by it, I realized a Steam release was in order. I took my time, but after sitting down and fixing some nasty bugs and others (white text on a white background? Really dude?) I am now happy to release it on Steam and let it be free with a nice, deserved final update. I hope you enjoy it. Take care.['English']['English']NaNTrueFalseFalse0000NaN00NaN0000MCAMCASingle-playerAdventure,SimulationNaN
8493Path of SurvivorsJan 8, 20240 - 0003.990Path of Survivors is a multi-class auto-battler survival game with roguelite elements. Demo save data will carry over to the full version! You can have up to six playable characters on your team auto-battling their way through hundreds of mobs on the screen Plan your path in the 1000+ nodes passive tree Pick ability altering rewards to spice up the run after defeating bosses Craft gear to help your battlers survive in this fast paced world Earn experience and loot to help you prepare for the next run. Various playing modes available to suit your needs (fully auto, all manual, or a mix)['English'][]NaNTrueFalseFalse0000NaN340NaN0000Limited InputLimited InputSingle-player,Steam Achievements,Partial Controller Support,Steam CloudAction,Casual,Indie,RPG,SimulationNaN
8494The Night HeistJan 5, 20240 - 0009.990Meet Mariah, Maria, and Missy a group of college girls from Whitson Community College, however like most people who attend college find themselves also working a part-time job trying to pay off their student loans and other bills. For Mariah, working part time at a shop wasn’t enough. She wanted more. More money to not only pay off her loans and bills but for other things she and the girls wanted. So Mariah and the girls take things into their own hands and began robbing houses at night. Calling it. The Night Heist. In this Visual Novel you will follow Mariah and her friends as they try to pull off the perfect heist. But it won't be as easy as you may think. (FREE DLC) Content: Includes another visual novel story following a girl name Grace who has a best friend name Hector who happens to have a crush on her. But Grace has a secret she hasn't told Hector. She's a God. But their way more to the story your gonna have to find out with CHOICE DECISIONS which may or may not affect Grace's life while you play. Play (Grace) to find out what happens next. 'This game is a visual novel based off the book series which shares the same title as the game.'['English']['English']NaNTrueFalseFalse0000NaN120NaN0000Ladell ParksLadell ParksSingle-player,Steam Achievements,Full controller supportCasual,IndieNaN

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NameRelease dateEstimated ownersPeak CCURequired agePriceDLC countAbout the gameSupported languagesFull audio languagesReviewsWindowsMacLinuxMetacritic scoreUser scorePositiveNegativeScore rankAchievementsRecommendationsNotesAverage playtime foreverAverage playtime two weeksMedian playtime foreverMedian playtime two weeksDevelopersPublishersCategoriesGenresTags# duplicates
2Jewel Quest PackAug 24, 20090 - 200000019.990Includes the first three titles in the the ultimate jewel matching adventure, Jewel Quest ! Rupert and Emma have settled down and opened a museum to display their many artifacts. While playing with a mysterious jewel board, their daughter unknowingly pops open a secret compartment. Suddenly, the air is filled with spores, and Natalie's vision fades. Desperate to save their daughter's sight, Rupert and Emma search the globe in search of the fabled Golden Jewel Board, rumored to hold the antidote that will cure her, but does it even exist? Guided by cryptic clues left by a shady stranger, Rupert and Emma encounter new challenges; wild monkeys to capture, powerful pearls that can alter the jewel boards, and head-to-head competition that pit you against renowned experts, Hani and Sebastian. Time is running out! It's up to you to follow the clues and find the cure! 200 levels in 11 regions 30 different jewels Visit every continent, while working on quests to earn jewels and artifacts Search for the fabled Golden Jewel Board Join Professor Pack on the ultimate jewel matching adventure across the world's richest continent. The dangers of the safari, The history of the Zimbabwe ruins and the majesty of Victoria Falls await your discovery, filled with puzzles of skill and twists, while surrounded by gorgeous dynamic backdrops and animation. Get swept away by the heart pounding soundtrack as you're immersed in realistic and authentic African settings. Discover an amazing new element of fun with the Exclusive Dueling Jewels Tournament Play: Pit your jewel matching skills against others around the world! Play against other players, or be matched with a computer opponent! Embark on a thrilling journey in a story filled with adventure, love, and betrayal that changes with every replay! Map your progress through 180 challenging puzzles Encounter buried relics, cursed items, and mind-boggling boards Stunning graphics, captivating music, and wild sounds Get special hints to help you with your battle against time Explore the ancient ruins of Mayan civilization while discovering hidden treasures and priceless artifacts. In this unique new take on the classic-style matching game, you must rearrange valuable relics to turn sand tiles into gold. When all of the tiles in a puzzle board are golden, you win! As you venture deeper into the jungle, you will encounter increasingly difficult puzzles containing secret twists, cursed items, and buried artifacts. Earn the respect of your fellow archaeologists and collect oodles of treasure and jewels!['English'][]NaNTrueFalseFalse00193NaN00NaN0000iWiniWinSingle-playerCasualCasual,Puzzle,Match 33
0EA SPORTS FC™ 24Sep 28, 20230 - 200000069.990This game includes optional in-game purchases of virtual currency that can be used to acquire virtual in-game items, including a random selection of virtual in-game items. FC Points not available in Belgium.['English', 'French', 'Italian', 'German', 'Spanish - Spain', 'Japanese', 'Korean', 'Polish', 'Portuguese - Brazil', 'Simplified Chinese', 'Spanish - Latin America', 'Traditional Chinese', 'Arabic', 'Czech', 'Danish', 'Dutch', 'Norwegian', 'Portuguese - Portugal', 'Russian', 'Swedish', 'Turkish']['English', 'French', 'Italian', 'German', 'Spanish - Spain', 'Japanese', 'Polish', 'Portuguese - Brazil', 'Simplified Chinese', 'Spanish - Latin America', 'Arabic', 'Dutch', 'Russian', 'Turkish']NaNTrueFalseFalse0000NaN4022263NaN0000EA Canada & EA RomaniaElectronic ArtsSingle-player,Multi-player,PvP,Online PvP,Shared/Split Screen PvP,Co-op,Online Co-op,Shared/Split Screen Co-op,Shared/Split Screen,Cross-Platform Multiplayer,Steam Achievements,Full controller support,In-App Purchases,Remote Play Together,HDR availableSimulation,SportsNaN2
1Freeze Tag Fun Pack #1Sep 23, 20090 - 200000019.990img.border { border: 0px solid #333333 ; padding: 7px 15px 7px 7px ; } Traverse a map of an ancient land and solve plenty of puzzles on the way. Control the chameleon idol and, using its magic power, blast gems before they reach the hole. At the end of each level, the score is converted to money that you can spend at the shop to buy extra lives or new skins for the chameleon. Each skin comes with different powerups and effects. More than 100 levels Amazing graphics in full 3D 18 different skins for your chameleon Dynamic high score tracking in the game High quality soundtrack Catch a boatload of fishy fun in this original arcade challenge! Load up the RV and crisscross the country in a series of tournaments that will put your angling prowess to the test. Cast your line in colorful locations like Bullhorn Lake, Golden Corn Lake, and Wicked Mansion Lake. Catch fish to earn points and climb to the top of the rankings in the amateur, pro, and elite circuits. Your fellow fishers are sure to keep you on your toes, but watch out for surprises swimming just below the surface that will slow you down. Featuring innovative gameplay, colorful full-screen graphics, and hours of fun for the whole family, Fishing Craze is no fish-tale, it's the real thing! Catch it today! Unlimited Play Amateur, Pro, and Elite Tournaments Wide variety of fish to catch Six sets of characters to use Bright and colorful full-screen graphics Breed baby animals and nurture their growth inside an amusing pet shop. As a boutique owner, you must work hard while maintaining a great sense of humor. Raise eight kinds of animals to make healthy, vivacious pets for loving owners. Buy appropriate items for particular breeds and work to unlock all items in the shop`s interior. Check the pet sales report frequently to be a smart business owner, and build the Pets Fun House empire. Unlimited, unrestricted gameplay Access all 35 fun pet shop levels Access all 5 card game levels Raise all 8 kinds of pets in the shop Unlock items in the shop's interior page Unlock 6 items in Pet Shop Supplies page Help amazing toy robot Xango find his upgrade parts in this brain-stretching, 3D animated action puzzler adventure. Three game modes guarantee many hours of action, puzzling and relaxing fun. Match three colored crates and watch ‘em explode in Classic mode. Solve brain-twisting puzzles in Puzzle mode. Play without time pressure in Relax mode. Exotic landscapes, lively tango music and wacky dances make Xango Tango fun for the whole family. Help Xango find all of his parts to see the surprise ending! Unlimited Play Three game modes: Classic, Puzzle and Relax 48 exotic scenes and 12 exciting power-ups in Classic mode 48 different challenges in Puzzle mode Endless play in Relax mode 3D animations and graphics Surprise ending['English'][]NaNTrueFalseFalse0000NaN00NaN0000Freeze Tag Inc.,Joju Games,Linksolutions Ltd.,Dekovir EntertainmentFreeze Tag Inc.Single-playerCasualNaN2
3Mahjong Quest CollectionAug 24, 20090 - 20000009.990Includes the first three installments of Mahjong Quest , the epic tale of tile matchmaking! What's the meaning of happiness? You are Kwazi. Starting from a mysterious birth at a mountaintop monastery and ending as a wizened old man, you use your grandfather's ancient Mah Jong set to solve an ever-challenging series of puzzles. As you play Mah Jong Quest 3, you'll make life choices that take you though battles against dragons, unreturned love, twisty career paths, artistic fulfillment, utter devastation, spiritual awakening, a rebuilding, and ultimately a blossoming family. The story unfolds based on the decisions you make, so choose wisely. In the end, only you can match the tiles and find the balance that brings about true Happiness. Unlimited Play Four Game Modes: Quest, Freeplay, Tournament, and Variations 72 Challenging Levels in Quest Mode More than 800 New Puzzles Hundreds of Classic Layouts Nature has struck back. The world has fallen into a state of imbalance, splitting our teenage here Kwazi into the male Kwazi White and Female Kwazi Black. You must help the Kwazis advance through the eight mystical lands, matching pairs and triplets like never before. Only you can restore harmony to the world. 8 lands with 8 levels each in Kwazi's Quest, each with it's own special tiles Over 500 new puzzles Dozens of special tiles and monstrous surprises! NEW Tournament mode! 32 unique puzzles Play against competitors on-line Mind-blowing animation! Over 144 classic layouts Unlimited game play! Play as long as you live - forever! More than an addictive puzzle game - a true cinematic experience. After three dragons wreak havoc over the empire, young Kwazi must use an ancient set of Mah Jong tiles to restore balance. Enjoy sweeping animations as you help Kwazi journey through the Orient, meet wise animal guides, and use an amazing array of special tiles to solve tricky puzzles. In addition to this great story, you can also enjoy your favorite layouts in Classic-style play, and whole new challenges in Puzzle-style play. Reveal unique tiles that provide special powers Classic Play: over 80 classic layouts, endlessly replayable with unlimited shuffles Puzzle Play: more incredible power tiles and 80 more brain-teasing layouts Play your favorite layouts in special modes for stimulating challenges['English'][]NaNTrueFalseFalse00202NaN00NaN0000iWiniWinSingle-playerCasualCasual,Puzzle2
4Wallace & Gromit’s Grand AdventuresMar 23, 20090 - 200000014.990Enter the colorful world of West Wallaby Street in a series of four cracking adventures brought to you by Aardman Animations, the creators of the Wallace &amp; Gromit animated films, and award-winning Telltale Games. As with the brilliant Aardman films, each Wallace &amp; Gromit episode finds the earnest inventor and his faithful canine companion embarking on ambitious new ventures laced with unexpected (and always laugh-inducing) complications. Giant bees, kidnapped dogs, a beach resort in the cellar and the finale at the Prickly Thicket country club. Take the duo through trials and tribulations to set things right by tea time! Episode 1 – 'Fright Of the Bumblebees” Wallace attempts to save his bumbling honey business with supersized flowers. This leads to an unintended consequence - giant bees! - and Gromit must save the town from the angry swarm! Episode 2 – “The Last Resort” Wallace &amp; Gromit turn their basement into a beach resort when rains derail their holiday plans. After a resort guest gets bonked by an unknown assailant, Gromit and the deduct-o-matic invention must solve the case! Episode 3 – “Muzzled!” Town newcomer Monty Muzzle is holding a fundraiser to rebuild the local dog shelter. Gromit discovers that Muzzle's intentions aren't exactly charitable, and he must foil Muzzle's plot and rescue his canine friends. Episode 4 – “The Bogey Man” Wallace has been admitted to Prickly Thicket, the oldest country club in Lancashire. Wallace and his faithful caddie Gromit get caught up in a club dispute, then must fight to save all they hold dear!['English (full audio)', 'French', 'German', 'Italian', 'Spanish - Spain', 'English']['English']NaNTrueFalseFalse0000NaN00NaN0000TelltaleTelltaleSingle-playerAdventureNaN2